Supervisor

Suitable for

Abstract

Co-supervised by Systems Security Lab

Due to an increase in the availability of off-the-shelf radio hardware, signal spoofing and replay attacks on satellite ground systems have become more accessible than ever. This is particularly a problem for legacy systems, many of which do not offer cryptographic security and cannot be patched to support novel security measures.

One method to protect against these attacks is transmitter fingerprinting: identifying transmitters by analysing small differences in the transmitter hardware, expressed in the radio signal. This can be used to distinguish legitimate transmitters from one another, or to identify attacker-controlled transmitters at ground level.

In this project a student would build upon existing work in satellite transmitter fingerprinting. This will involve setting up data collection hardware and software to receive and process messages from a satellite constellation, using this data to train machine learning models, and comparing to existing results.

See also https://arxiv.org/pdf/2305.06947.pdf (current work)

https://github.com/ssloxford/SatIQ

Pre-requisites: Experience with radio hardware, signal processing, and/or machine learning would be useful for this project.